chrbr

Got it.

I know nothing about the reasoning behind the original decision from Synology, nor the internal politics at play, but typically the customer support tail is not wagging the dog of the rest of the company. Might be bias/anecdata from the places I've worked, but product usually drives everything, and the support staff has to deal with the consequences.

F1TV had some fun with it in their usual post-race programming: Joylon Palmer (F1TV announcer) did a deadpan "breakdown" of the Lego race during his segment, and Sam Collins analyzed the aerodynamics of the Lego cars in his.

The drivers all said it was the best driver's parade they've been in. I don't know how marketing like this works, and if it was worth it for Lego in the end, but what a masterstroke. Lots of fun organic mentions of Lego over the past week because of it.

This is what I don't get. We don't have masses of unemployed people waiting in the ranks to fill a large amount of new jobs, as unlikely an outcome as that even is. Which means any large uptick in people working in manufacturing would have to come from some other industry. So what jobs would we give up for it?

Yeah, we've used CAPTCHAs to great effect as gracefully-degraded service protection for unauthenticated form submissions. When we detect that a particular form is being spammed, we automatically flip on a feature flag for it to require CAPTCHAs to submit, and the flood immediately stops. Definitely saves our databases from being pummeled, and I haven't seen a scenario since we implemented it a few years ago where the CAPTCHA didn't help immediately.

Reminds me of the advice around the deadbolt on your house - it won't stop a determined attacker, but it will deter less-determined ones.

The paper calls out a few things that they didn't cover:

> The CCC+TL model predicts the age of the Universe as 26.7 Gyr against the generally accepted value of 13.8 Gyr. This is of deep concern and needs the model validation against multiple observations, including BAOs, CMB, Big Bang nucleosynthesis (BBN), and globular cluster ages. Our focus here is on BAOs.

I am not in academia and therefore am not qualified to have strong opinions on any of this, but I do like the idea of papers not swinging for home runs all the time by explaining everything, and instead being happy with hitting a single by proposing something intriguing and asking for others to chime in.

Unfamiliar with academia here, and I can't quite figure it out from TFA - does a retraction always imply wrongdoing, instead of mere "wrongness?" Or are papers sometimes retracted for being egregiously wrong, even if their methods were not intentionally misleading?

The entire home-buying process (in the US, at least) seems to be built on shady-looking ways to nickel and dime people. I remember telling friends when going through it that it'd be easy to scam me because I got so used to urgent requests to pay some fee for inspections or legal stuff or whatever that I'd just shell out the money without asking questions.

Yeah, I like that improvement/clarification. Good assertion. Now I wonder if it changes my stance: are the path modern LLMs are on ever going to replicate this environment for acquiring new information that humans currently operate in?

I agree. A thought experiment I had recently:

Let's say we could somehow train an LLM on all written and spoken language from the western Roman civilization (Republic + Western Empire, up until 476 AD/CE, just so I don't muddy the experiment with near-modern timelines). Would it, without novel information from humans, ever be able to spit out a correct predecessor of modern science like atomic theory? What about steam power, would that be feasible since Romans were toying with it? How far back do we have to go on the tech tree for such an LLM be able to "discover" something novel or generate useful new information?

My thought is that the LLM would forever be "stuck" in the knowledge of the era it was trained in. Something in the complexity of human brains working together is what drives new information. We can continue training new LLMs with new information, and LLMs might be able to find new patterns in data that humans can't see and can augment our work, but the LLM's capability for novelty is stuck on a complexity treadmill, rooted in its training data.

I don't view this ability of humans as some magic consciousness, just a system so complex to us right now that we can't fully understand or re-create it. If we're stochastic parrots, we seem to be ones that are magnitudes more powerful and unpredictable than current LLMs, and maybe even constructed in a way that our current technology path can't hope to replicate.